Lead Product Manager, AI Platform

Job Description

Disney Experiences Technology is looking for a Lead Product Manager, AI Platform to join the AI Center of Excellence within DX Tech & Digital. This role sits inside a Product Engineering pod focused on building and scaling the internal AI Platform that powers next-generation intelligent solutions across Disney's Parks, Resorts, and Vacation brands worldwide, including Disney Cruise Line and Aulani. You'll own the full journey from an initial stakeholder conversation to a shipped, working AI capability — scoping, building, evaluating, and deciding when to graduate, harden, or retire the work.

This is a senior individual contributor role reporting to the Senior Manager, AI Platform. You'll operate independently of the standard sprint cycle, working directly with internal stakeholders without a PM intermediary, while setting technical direction and mentoring adjacent engineers and PMs — without formal direct reports.

Key Responsibilities

• Take internal stakeholder requests from first conversation to shipped AI capability — owning discovery, scoping, design, build, and rollout end-to-end
• Build AI-native workflows on the internal AI Platform stack, including prompts, agents, retrieval pipelines, and evaluation harnesses
• Set the technical direction for the Product Engineering pod, including prototyping standards and shared tooling
• Make product and architecture decisions independently in a low-structure environment — knowing when to cut scope, ship, or ask for input
• Share work-in-progress at roughly 70% complete to gather stakeholder feedback quickly rather than waiting until it's polished
• Instrument prototypes with evaluation frameworks to determine whether a capability is earning its place, then graduate, harden, or retire it deliberately
• Build prototypes, demos, and mockups that validate emerging platform patterns and serve as reference implementations
• Mentor adjacent engineers and PMs on AI prototyping and outcome-driven development
• Drive cross-team alignment with platform engineers, AI ops, and security/compliance partners through influence rather than authority
• Translate technical tradeoffs into clear recommendations for senior stakeholders, connecting platform capability to measurable business outcomes

Requirements

• Bachelor's degree in Computer Science, Information Systems, Software, Electrical/Electronics Engineering, or a comparable field, or equivalent work experience
• 7+ years of combined experience across software engineering and product roles in technical or AI-platform contexts
• Production experience with LLM-powered applications, including advanced prompt engineering, agent frameworks, evaluation pipelines, and retrieval-augmented generation (RAG)
• Hands-on technical ability to scope, build, and ship a working prototype end-to-end — comfortable in Python and modern AI tooling without engineering or PM handoff
• Demonstrated experience turning ambiguous stakeholder requests into working systems, including direct user conversations
• Track record of taking products or capabilities from 0 → 1 inside an enterprise or platform environment with measurable adoption
• Hands-on production experience with at least one LLM gateway (LiteLLM, OpenRouter, Bedrock, or equivalent), one workflow/agent runtime (n8n, LangGraph, Temporal, or equivalent), and one evaluation/observability framework (Arize, Phoenix, Langfuse, or equivalent)
• Strong judgment on scope, speed, and quality tradeoffs
• Track record of driving cross-team outcomes through influence, not authority
• Excellent communication skills, including translating AI capability into business outcomes for senior stakeholders

Preferred

• Background as a forward-deployed engineer, applied AI engineer, or product-minded engineer at an AI-native company
• Direct production experience with MCP (Model Context Protocol), OpenWebUI, n8n, or LiteLLM
• History shipping deliberately scrappy prototypes for fast stakeholder learning
• Familiarity with enterprise security, compliance, and governance patterns for AI systems
• Experience instrumenting AI products with eval frameworks and observability tooling
• Background partnering with non-technical senior leaders to decompose business problems into shipped AI capabilities